simulate_trials: Perform simulations of time-to-event data using arbitrary...

In gestate: Generalised Survival Trial Assessment Tool Environment

Description

Function for simulating generalised two-arm time-to-event trial data for NPH trials with arbitrary event, censoring and recruitment distributions.
Event and censoring distributions are specified via Curve objects, with recruitment specified through an RCurve object. As it uses same architecture and similar syntax to nph_traj(), analysis results ought to be directly comparable. It is designed to complement nph_traj(), either as a stochastic alternative, or as a means to validate its outputs. It can also be used to build more complex simulations by combining the outputs of multiple runs; e.g. multi-arm trials.
Data sets created by this function are formatted so they may be automatically recognised and analysed by analyse_sim().

Usage

simulate_trials(
  active_ecurve,
  control_ecurve,
  active_dcurve = Blank(),
  control_dcurve = Blank(),
  rcurve,
  assess = NULL,
  fix_events = NULL,
  iterations,
  seed,
  detailed_output = FALSE,
  output_type = c("matrix", "list")
)

Arguments

active_ecurve	Event distribution for the active arm, specified as a Curve object
control_ecurve	Event distribution for the control arm, specified as a Curve object
active_dcurve	Dropout/censoring distribution for the active arm, specified as a Curve object. By default, Blank(), i.e. no dropout.
control_dcurve	Dropout/censoring distribution for the control arm, specified as a Curve object. By default, Blank(), i.e. no dropout.
rcurve	Recruitment distribution, specified as an RCurve object
assess	Positive number for the assessment time at which administrative censoring will be performed.
fix_events	Positive integer for the number of events to fix (if required), letting the assessment time vary. Alternatively, NULL for fixed time assessment with variable event numbers. Notes: Fixing event numbers overrides any specified assessment time and slows simulation considerably. Default = NULL (fixed analysis time)
iterations	Number of simulations to perform. Depending on trial size, 10,000-20,000 is typically OK to analyse on 8GB RAM.
seed	Seed number to use. Numerical, although if "Rand" is specified, a system-time-derived number will be used.
detailed_output	Boolean to require full details of timings of competing processes. If FALSE, the simplified data only includes the *'ed output columns - this approximately halves RAM requirements. Default=FALSE (simplified).
output_type	"matrix" or "list" specifying the type of output required. "matrix" requests a single matrix with a column "iter" to denote the simulation, while "list" creates a list with one entry per simulation. Default="matrix".

Value

Returns a table with one row per patient per simulation. Table contains the following columns:

• "Time" Simulated actually observed (patient) time of event or censoring: This is the main column of interest for analysis*

• "Censored" Simulated censoring indicator: 1 denotes censoring (administrative or dropout), 0 denotes an event*

• "Trt" Treatment group number - 1 is active, 2 is control*

• "Iter" Simulation number*

• "ETime" Simulated actual event (patient) time (may or may not be observed)

• "CTime" Simulated actual censoring/dropout (patient) time (may or may not be observed)

• "Rec_Time" Simulated (trial) time of recruitment

• "Assess" Prespecified (trial) time of assessment

• "RCTime" Simulated actual administrative censoring (patient) time (may or may not be observed)

Author(s)

James Bell

Examples

example_sim <- simulate_trials(active_ecurve=Weibull(250,0.8),control_ecurve=Weibull(100,1),
rcurve=LinearR(12,100,100), assess=20, iterations=5,seed=12345)

Example output

gestate documentation built on Feb. 20, 2020, 5:08 p.m.